The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

The practice of self medication is continuously increasing worldwide due to its important roles in curing minor conditions or symptoms. This study was conducted to evaluate the factors associated with self medication practice of Iraqi respondents residing in Baghdad City. This study was designed as cross sectional study in which data was collected via direct interviews with respondents using a previously prepared questionnaire. This study investigated 348 respondents from different age groups. The majority of respondents were male aged between 30-60 years, married with secondary or academic level of education and employed with accepted monthly income. The main reason for practicing self medication was previous experience with the same condi

Objective: is to determine the level of awareness concerning the reproductive health among adolescent girls in
Baghdad City.
Methodology: A cross sectional study was performed in order to assess the level of awareness regarding reproductive
health among 180 adolescent school girls in the age 12-18 years from five secondary schools in Al-Seder Sector in
Baghdad city, the data was collected by direct interview using constructed questionnaire to obtain socio-demographic
characteristics and level of awareness related to reproductive health. The study started from September 2012 to
January 2013.
Results: the results show that the highest percentage of girls (47.7%) was in age (17-18) year's age, (54.5%) at 4th class
se

Pregnancy at an early age of life is a major challenge. The consequences of this problem have an impact on the quality of life of the young mother and her family, and determines an important risk for her offspring. The son of a teenage mother has, in general, greater risks than that of a mother of more than 20 years. The aim of this study is to determine the prevalence and outcome of teenage pregnancy. A descriptive data base study was conducted at Al-Elwia Maternity Teaching hospital in the period from January 1, 2019 to the end of June 2019 within the age between 12 and 19 years old. The mean age of the mother was 17.4 ±1.5 years. The mean age of the father was 23.9 ± 5.7 years with (69.5%) with Vaginal delivery and most of the

Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

The research aims to improve operational performance through the application of the Holonic Manufacturing System (HMS) in the rubber products factory in Najaf. The problem was diagnosed with the weakness of the manufacturing system in the factory to meet customers' demands on time within the available resources of machines and workers, which led to time delays of Processing and delivery, increased costs, and reduced flexibility in the factory, A case study methodology used to identify the reality of the manufacturing system and the actual operational performance in the factory. The simulation was used to represent the proposed (HMS) by using (Excel 2010) based on the actual data and calculate the operational performance measures

This research aims to address the most recent international standard in the field of insurance contracts, the International Financial Reporting Standard (IFRS17) and the theoretical framework of the standard in addition to the most important characteristics of the standard (IFRS17), as well as to identify the paragraphs of the modern standard, with the challenges its application in general and the use of the approach (inputs - operations - outputs) to present the challenges of its application in the Iraqi environment and specifically in the environment of Iraqi insurance sector companies (government), the research is based on the main premise that the identification of the requirements for the application of the International Fin

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv